CTCF controls three-dimensional enhancer network underlying the inflammatory response of bone marrow-derived dendritic cells

Dendritic cells are antigen-presenting cells orchestrating innate and adaptive immunity. The crucial role of transcription factors and histone modifications in the transcriptional regulation of dendritic cells has been extensively studied. However, it is not been well understood whether and how three-dimensional chromatin folding controls gene expression in dendritic cells. Here we demonstrate that activation of bone marrow-derived dendritic cells induces extensive reprogramming of chromatin looping as well as enhancer activity, both of which are implicated in the dynamic changes in gene expression. Interestingly, depletion of CTCF attenuates GM-CSF-mediated JAK2/STAT5 signaling, resulting in defective NF-κB activation. Moreover, CTCF is necessary for establishing NF-κB-dependent chromatin interactions and maximal expression of pro-inflammatory cytokines, which prime Th1 and Th17 cell differentiation. Collectively, our study provides mechanistic insights into how three-dimensional enhancer networks control gene expression during bone marrow-derived dendritic cells activation, and offers an integrative view of the complex activities of CTCF in the inflammatory response of bone marrow-derived dendritic cells.

Finally, in Figure 7c. it is a little misleading for the authors to selectively show gene ontology analysis for only CTCF-dependent RelA target genes. A similar analysis is needed between LPS stimulated WT cells and un-stimulated WT cells, which would allow for the knowledge that whether CTCF deficiency has a selective effect on pro-inflammatory cytokine genes or unbiased diminishes all induced gene expression.
Reviewer #2 (Remarks to the Author): In this well-written manuscript, Yang et al. examined the effects of depletion of the chromatin structural protein CTCF on gene regulation in dendritic cells. They found that CTCF is dispensable for GM-CSF mediated differentiation of dendritic cells, but elegantly showed key structural and transcription effects downstream of CTCF depletion. The authors used these observations of aberrant transcription and structure after CTCF knockout as rationale to further examine chromatin features in dendritic cells. A notable experiment includes measurement of H3K27ac regions plus their relevant chromatin interactions using HiChIP, a very new technique. This experiment revealed chromatin structural links between enhancers and promoters in wild-type cells and those activated with LPS, in addition to CTCF knockout cells. The authors also explored STAT5 binding to understand how JAK/STAT signaling may play a role in transcriptional regulation in the CTCF knockout, and used ChIP-seq to examine RelA (subunit of NF-kB) binding along the genome and determine its structural context in activated cells (using RelA HiChIP) or in the CTCF knockout (using H3K27ac HiChIP).
This study has important implications within the field of gene regulation, but also within the field of immunology. The methods are very close to the cutting edge of the chromatin field and are clearly written. Overall, the study was modestly descriptive but could be made publishable by addressing experimental concerns below, mainly the question of whether reintroduction of CTCF into CTCFdepleted cells would revert the chromatin structural changes observed in the CTCF knockout.

Major comments:
Could the authors rescue CTCF levels in the knockout cells by reintroducing CTCF via an expression vector? This would answer the question of whether chromatin structure (TADs, insulation boundaries, loops, enhancer-gene interactions) reverts back to normal?
The dispensability of CTCF for activation of BMDCs is an interesting observation. What are the other mechanisms by which BMDC activation is orchestrated? If these mechanisms are inhibited, does CTCF depletion worsen the phenotype? What is the rationale for continuing with the chromatin architecture study if CTCF is dispensable for BMDC activation?
The experimental data from Figure 4 helps answer a key question of whether CTCF mediates distal enhancer loops within TADs in dendritic cells and whether disruption of chromatin structure by CTCF depletion results in cross-TAD interactions and subsequent transcriptional change. Well done.
A supplementary table naming the genes whose interaction and transcription become disrupted with CTCF knockout from Figure 4F would help the reader understand which types/classes of genes have their structure and transcription preserved by CTCF in the normal context. Is Aldh1a2 an important gene within the context of the authors' studies?
Does the normal expression of the two genes (Trim25 and Irak2) in Figure 5H get rescued if the STAT5 is overexpressed in CTCF knockout cells? This would help determine whether STAT5 activity can override CTCF depletion-mediated chromatin structural defects to preserve normal transcription of CTCF-dependent genes.
The bottom of Supplementary Figure 6 and Figure 7F provide specific evidence to suggest that RelA acts not only as a transcription factor, but as a factor found at enhancers that can may affect transcription. Does this RelA HiChIP interaction profile not appear within wild type cells (not LPS treated)? What was the rationale for only measuring chromatin structure via HiChIP in the LPS treated wild-type cells only? Figure 8 shows an interesting observation. Since the manuscript focuses on chromatin structure and gene regulation in dendritic cells, the authors may consider examining chromatin structure at IL12 and IL6 downstream target gene loci in CTCF knockout cells and in CTCF knockout + IL12/6 cells, to understand what is going on at these loci when additional IL12 or IL6 is introduced into the system.

Minor comments:
To ensure the reproducibility of the results, the authors should include catalog numbers for all relevant antibodies/reagents used in this study.
Signal quantifications and molecular weight markers, in addition to an indication of the n for each Western blot, would be useful.
In general, graph titles would be helpful for those that want to quickly examine the figures.
How were the ChIP-seq tracks generated?
Representative region shown in Figure 1E  , and these two studies seem to be good ones to reference within the context of the current manuscript.
In Supplementary Figure 3A, the authors could probably show the same maximum values within the different groups of 4 heatmaps, to show more clearly that TAD structure is weakened with the CTCF knockout.
For a couple of columns in Supplemental Figure 4A-B, the numbers add up to greater than 100%. Please clarify these figures. Some rationale for gene selection for Figure 3F would help the reader understand why each gene's interaction/transcription change is important for the resultant phenotype after LPS.
How do the authors define loops gained in CTCF knockout in Figure 4? Are they still examining HiChIP data? Figure 4H should have an indication of the n for the experiment, and Figure 4I needs molecular weight markers and an indication of how many blots were performed.
Supplemental Figure 5E does not show a log2(fold-change). Is this an RT-qPCR experiment?
The analysis in Figure 5G is very useful to the reader and is a great example of how to dive deeper into Gene Ontology analyses. Are these all the genes in the "Regulation of NF-kB activity" term? If not, it would be useful to see all of them together on the graph.

COMMENTS FROM REVIEWER #1
Comment #1: The paper examines GM-DC development in an inducible CTCF depletion model. This system uses the GMCSF-derived cells used in many studies. The author claim from this (based on the data in Supplemental Figure 2) that CTCF is not required for GM-DC development. However, in the field of dendritic cells, it is now known based on an important Resource Immunity paper published in 2015 that mouse BM cells cultured with GM-CSF alone are heterogeneous, and contain mixtures of monocyte-derived DCs and monocyte-derived macrophages (Helft et al, Immunity 2015). This is not a paper that can be ignored, as it has been cited 279 times in the last 6 years. This study basically transformed the field by making it necessary to evaluate such cultures in terms of what cells might be affected by different conditions. Thus, in this case, it would be important for the authors to examine whether the CTCF depletion specifically impaired the development of one of these populations, which leads to the overall 50% reduction of total cell number. Since these two populations show completely different phenotypes, for example by FACS analysis, in the expression level of MHC-II and co-stimulatory molecules.
Ion this system, only DCs express co-stimulatory molecules, while MACs do not. Thus, the authors need to examine whether the two populations are individually affected by the loss of CTCF. For example, it could be the case that in the absence of CTCF, one population develops normally, but the other does not develop. Alternately, the impact of CTCF depletion on various genes could be different between the DCs and the MACs. This possible differential effect could also true for the apoptosis and proliferation assays, and their capacity for antigen uptake and induction of T cell proliferation. These analyses would be necessary to draw the conclusion that "CTCF is dispensable for GM-CSF-mediated differentiation of DC in vitro". Also, throughout the paper, the authors use the term DC. This should be corrected systematically, which in fact is not possible, as GM-DCs are already known to be heterogeneous. Nonetheless, the authors need to replace the "DC" with another more precise term, and I might suggest GM-DC/Macs until they have the new analysis showing the data independently for each type of cell. In summary, the analysis and conclusions need to be reformulated by taking into account the fact that the authors data at present is a bulk analysis of at least two different types of cells.

Response #1:
We thank the reviewer for addressing this important point. As suggested, we performed

Comment #2:
A second problem here is that of novelty and priority. The claim by the authors that "CTCF is dispensable for higher order chromatin compartment but essential for TAD organization" and that CTCF is required for maintaining "intra-TAD chromatin looping" have already been published in 2017 by Nora et al. in Cell, in a slightly different technique using auxin-inducible degron system, and in mouse ES cells. Thus, while the authors do extend the conclusions into another cell type, the problem that the cell type is mixed and may not apply to both DCs and MACs is a problem. The authors here use a tamoxifen-inducible Cre system in GM-DC and get similar conclusions, and while these are not new discoveries, they may be publishable in Nature Communications, but should not be allowed to be a sloppy paper by permitting the mixed cell analysis.

Response #2:
We thank the reviewer for this comment. Indeed, the claim that "CTCF is dispensable for higher order chromatin compartment but essential for TAD organization" and that "CTCF is required for maintaining intra-TAD chromatin looping" is not novel; accordingly, we have already cited several relevant papers in the Introduction and Discussion sections of the manuscript. Nonetheless, our study aimed to dissect the mechanism through which CTCF regulates the complex molecular events occurring in mouse primary DCs in response to pathogenic stimuli by analyzing the global transcriptomic, epigenetic, and topologic changes. Indeed, consistent with previous reports that used an auxin-inducible degron system to deplete CTCF in several cellular DCs. We hope that this explanation clarifies the reviewer's point.

Comment #3:
Another major problem with the study is that it draws a major conclusion of causality that has not been established. In short, the logical flaw may be that of the classical "true, true, but unrelated" type. Specifically, the authors find two different phenomenon, #1) that CTCF depletion results in reduced GM-CSF-induced JAK2/STAT5 signaling and defective LPSinduced NF-kB activation; and #2) that CTCF depletion results in reduced loop formation and enhancer activation. The authors conclude that phenomenon #1 causes phenomenon #2. However, it is equally possible that the causality is that #2 causes #1, or even that neither causes the other. There is no evidence in the study to draw any conclusion about the cause of either. If the authors wish to draw this conclusions, they need to test it specifically, by, for example, blocking NF-kB signaling by an independent technique, leaving CTCF intact, and then test for the loop formation and enhancer activation. As it is, the authors jump to their big conclusion that "NF-kB binding facilitate stronger enhancer-promoter interactions as well as higher enhancer activity" and spent two whole pages (lines 269-335) discussing it. Alternately the authors could drop this conclusion and discussion and simply report the independent findings, with a bit of limited speculation and discussion. That approach would not exceed the data.

Response #3:
We thank the reviewer for these critical comments. As requested, we blocked NF-kB signaling using JSH-23, which prevents the nuclear translocation of NF-kB RelA 14 while leaving CTCF intact (Fig. 8a and 8b), and then explored whether activation of NF-kB signaling could facilitate enhancer activation and loop formation (Fig. 8c-8f). First, H3K27ac ChIP-seq analysis demonstrated that enrichment of H3K27ac at RelA binding sites induced by LPS stimulation was almost completely abrogated by JSH-23 pre-treatment (Fig. 8c). Next, the RelA-mediated chromatin interactions (shown in Fig. 7a) were subject to differential H3K27ac HiChIP loop analysis, which revealed 346 gained loops and 295 lost loops due to LPS stimulation ( Supplementary Fig. 10a). Interestingly, these dynamic changes in RelA-mediated chromatin interactions induced by LPS stimulation were significantly attenuated by pre-treatment of the BMDCs with JSH-23 ( Fig. 8d). Further, RelA target genes (shown in Supplementary Fig. 9c) were analyzed by RNA-seq, which revealed 827 upregulated and 406 downregulated genes in response to LPS stimulation (Supplementary Fig. 10b). The extent of changes in the transcript abundance of these differentially expressed RelA target genes was significantly diminished by pre-treatment of the BMDCs with JSH-23 before LPS stimulation (Fig. 8e).

The best examples showing the effect of NF-kB inhibition on enhancer activation, loop
formation, and the resultant RNA expression profile were provided by Il6 and Il12a (Fig.   8f). LPS stimulation resulted in increased mRNA expression accompanied by enhanced H3K27ac levels upstream of Il6 and Il12a promoters, which were severely abrogated by pre-treatment of the BMDCs with JSH-23 (Fig. 8f). Moreover, V4C plot for H3K27ac HiChIP loop with the Il6 and Il12a promoter regions as anchor demonstrated that loop formation induced by LPS stimulation between promoters and RelA binding sites were also decreased by JSH-23 pre-treatment (Fig. 8f). Taken together, these results indicated that NF-kB signaling can control spatial enhancer-promoter proximity, as well as distal enhancer activities for the optimal expression of its target genes. We added these new data to the revised version of the manuscript ( Fig. 8 and Supplementary Fig. 10), and hope that these additional results clarify the reviewer's point.  Fig. 9e). Gene ontology analysis showed that these 403 genes were enriched in positive regulation of cytokine production and inflammatory-related pathways (Supplementary Fig. 9f). These data demonstrated that CTCF depletion in BMDCs compromises the expression of genes significantly related with inflammationassociated pathways, including pro-inflammatory cytokine production. We added these new data to the revised version of the manuscript (Supplemental Fig. 9e and 9f). This study has important implications within the field of gene regulation, but also within the field of immunology. The methods are very close to the cutting edge of the chromatin field and are clearly written. Overall, the study was modestly descriptive but could be made publishable by addressing experimental concerns below, mainly the question of whether reintroduction of CTCF into CTCF-depleted cells would revert the chromatin structural changes observed in the CTCF knockout.

WTL) (Supplementary
→ We sincerely thank the reviewer for the careful review of our manuscript.

Comment #1:
Could the authors rescue CTCF levels in the knockout cells by reintroducing CTCF via an expression vector? This would answer the question of whether chromatin structure (TADs, insulation boundaries, loops, enhancer-gene interactions) reverts back to normal?

Response #1:
We thank the reviewer for highlighting this important point, and we completely agree that the rescue of CTCF in CTCF knockout cells to validate its crucial role in hierarchical As an alternative way for depleting and rescuing CTCF, we could consider an auxin-inducible degron system that allows rapid and specific depletion of a mAID-tagged protein via proteasome-dependent degradation upon auxin treatment [11][12][13] . For example, Nora et al. 13   We thank the reviewer for this comment. In this study, we used an "in vitro BMDC differentiation model" to investigate the function of CTCF in the three-dimensional enhancer network underlying the inflammatory response of mouse primary DCs. Since Fig. 3). Given  Fig. 1). These results again validate the usefulness of our "in vitro BMDC differentiation model" for addressing DC biology. However, we would rather delete the statement describing that "CTCF is dispensable for GM-CSF-mediated differentiation of dendritic cell in vitro," considering the controversy over cellular identity and heterogeneity of GM-CSF BM cultures 4,10 . We hope that this explanation clarifies this reviewer's point.

Comment #3:
The experimental data from Figure 4 helps answer a key question of whether CTCF mediates distal enhancer loops within TADs in dendritic cells and whether disruption of chromatin structure by CTCF depletion results in cross-TAD interactions and subsequent transcriptional change. Well done.

Response #3:
We thank the reviewer for the appreciation of our work and the positive feedback.

Comment #4:
A supplementary table naming the genes whose interaction and transcription become disrupted with CTCF knockout from Figure 4F would help the reader understand which types/classes of genes have their structure and transcription preserved by CTCF in the normal context. Is Aldh1a2 an important gene within the context of the authors' studies?

Response #4:
We thank the reviewer for the suggestions. By combining in situ Hi-C, H3K27ac HiChIP, and RNA-seq data generated from WT and CTCF-deficient BMDCs, we were able to identify 123 genes which expression was upregulated, possibly due to the augmented enhancer-promoter interactions established de novo within the same TADs in the CTCFdeficient BMDCs (Fig. 4d-4f). As requested, the list of these genes was presented as Supplementary Table 5.
Aldh1a2, the third most upregulated gene among the identified genes, encodes the aldehyde dehydrogenase 1A2 enzyme that catalyzes the synthesis of retinoic acid from retinaldehyde 19 . Given the critical role of retinoic acid in the induction and suppression of Treg and Th17 differentiation 20-22 , respectively, increased expression and enhanced enzyme activity of Aldh1a2 in CTCF-deficient BMDCs (Fig. 4h-4j) may provide favorable conditions for the development of T cell tolerance, which will be explored in our next project to further support the distinct pathophysiological role of CTCF in DCmediated immune responses.

Comment #5:
Does the normal expression of the two genes (Trim25 and Irak2) in Figure 5H get rescued if the STAT5 is overexpressed in CTCF knockout cells? This would help determine whether STAT5 activity can override CTCF depletion-mediated chromatin structural defects to preserve normal transcription of CTCF-dependent genes.

Response #5:
We thank this reviewer for addressing this important point. One of the most interesting findings of our study was that depletion of CTCF attenuates the GM-CSF-mediated JAK2/STAT5 signals (Fig. 5a and 5b). Moreover, we identified 476 genes, including Trim25 and Irak2, whose expression was influenced by defective JAK2/STAT5 signaling ( Fig. 5c-5e Fig. 7b).
However, the rescue of Stat5 activity in CTCF-deficient BMDCs did not increase the mRNA expression of Trim25 and Irak2. These results suggested that downregulation of these Stat5 target genes in CTCF-deficient BMDCs was not simply due to attenuated Stat5 signaling, and that restoration of STAT5 activity was not sufficient to overcome the disrupted looping between enhancers and their target genes observed in CTCF-deficient BMDCs (Supplementary Fig. 7c). We added these new data to the revised version of the manuscript (Supplementary Fig. 7).  (Fig. 6b-6d). Moreover, ChIP-seq analysis revealed that LPS stimulation potently induced genome-wide chromatin binding of RelA in WT BMDCs but not in KO BMDCs (Fig. 6e-6g). Furthermore, the number of H3K27ac HiChIP loops overlapping with RelA ChIP-seq peaks at least at one of the loop anchors dramatically increased upon LPS stimulation in WT BMDCs but not in KO BMDCs (Fig. 6l) Comment #7: Figure 8 shows an interesting observation. Since the manuscript focuses on chromatin structure and gene regulation in dendritic cells, the authors may consider examining chromatin structure at IL12 and IL6 downstream target gene loci in CTCF knockout cells and in CTCF knockout + IL12/6 cells, to understand what is going on at these loci when additional IL12 or IL6 is introduced into the system.

Response #7:
We thank the reviewer for raising this interesting point. Naïve CD4 + T cells differentiate into diverse effector and regulatory subsets to orchestrate immunity and tolerance 25,26 . In addition to T cell intrinsic signals, the innate immune system actively instructs adaptive immunity through antigen presentation and immunoregulatory cytokine production 25,26 .
For example, DC-producing IL-12 supports Th1 development 27 , whereas DC-producing IL-6 supports Th17 development 28 . Given that production of IL-6 and IL-12 was impaired in CTCF-deficient BMDCs, we examined the capacity of CTCF-deficient BMDCs for T cell differentiation in in vitro BMDC/CD4 T cell-coculture conditions. Indeed, the reduced T cell differentiation was largely attributed to defective cytokine production in the CTCF-deficient BMDCs, since treatment with exogenous IL-12 and IL-6 significantly rescued Th1 and Th17 differentiation in CTCF-deficient BMDCs, respectively ( Fig. 9c and 9d). As pointed out by this reviewer, the chromatin structure at Il12 and Il6 downstream target gene loci, such as Ifng and Il17 loci, during CD4 + T cell differentiation has long been explored by many groups [29][30][31] . We agree that studying the effect of CTCF depletion on chromatin structure in CD4 + T cells is quite interesting and important. However, we sincerely hope that this reviewer appreciates the wealth of data and analyses provided and concurs that answering this question using CTCF-deficient CD4 + T cell is beyond the scope of our current manuscript.

minor review
Comment #8: To ensure the reproducibility of the results, the authors should include catalog numbers for all relevant antibodies/reagents used in this study.

Response #8:
We would like to thank the reviewer for this suggestion. We have now described the catalogue numbers for all relevant antibodies and reagents in the Methods section.

Comment #9:
Signal quantifications and molecular weight markers, in addition to an indication of the n for each Western blot, would be useful.

Response #9:
We thank the reviewer for the suggestion. Now, the signal quantifications, molecular weight markers, and the number of biological replicates for each Western blot have been described (Fig. 1c, 4i, 5a, 6a, 6d, and 8a) Comment #10: In general, graph titles would be helpful for those that want to quickly examine the figures.

Response #10:
We thank the reviewer for this suggestion. We have now labeled the graph titles for some of the figures, including Fig. 3a, 3b, 3c, 4a, 8d, and 8e.

Comment #11:
How were the ChIP-seq tracks generated?

Response #11:
Uniquely mapped reads were normalized using deeptools (version 3.3.0) with command line options "--normalizeUsing CPM --binSize 1" to visualize ChIP-seq signal at specific genomic loci by IGV (version 2.8.2). ChIP-seq heatmaps were generated using deepTools to show normalized read counts at the peak center ±2 kb. This information has been described in the "ChIP-Seq Data Processing" subsection of the Methods section of the revised manuscript.

Comment #12:
Representative region shown in Figure 1E

Response #13:
We thank the reviewer for this comment, and the indicated references were added to the Introduction section of the revised manuscript.

Comment #14:
In Supplementary Figure 3A, the authors could probably show the same maximum values within the different groups of 4 heatmaps, to show more clearly that TAD structure is weakened with the CTCF knockout.

Response #14:
We thank the reviewer for this comment. In the revised manuscript, the Hi-C contact maps at each resolution are shown with the same maximum signal in the matrix.

Comment #15:
For a couple of columns in Supplemental Figure 4A-B, the numbers add up to greater than 100%. Please clarify these figures.

Response #15:
We apologize for the lack of clarity in these figures. We have now changed the labels in Supplementary Fig. 4a and 4b, as shown below.

Comment #16:
Some rationale for gene selection for Figure 3F would help the reader understand why each gene's interaction/transcription change is important for the resultant phenotype after LPS.

Response #16:
We thank the reviewer for raising this point. We believe that this comment is based on a misunderstanding that we may have caused due to inaccurate description of the legend of Fig. 3f. We have changed this legend in the revised manscript as follows: "Log2-fold changes in RNA expression for typical genes representing each regulatory mode shown in (c)," not in (d). Fig. 3f and 3g were selected as examples of six possible regulatory modes (Fig. 3c) controlling LPS-stimulated gene expression (Fig. 3e) Fig. 3f and   3g).

Comment #17:
How do the authors define loops gained in CTCF knockout in Figure 4? Are they still examining HiChIP data?

Response #17:
We thank the reviewer for indicating the lack of clarity in our description of loops in Fig.   4. As in the case for LPS stimulation in Fig. 3, differential analysis of chromatin interactions between WT and KO BMDCs were performed using H3K27ac HiChIP data to define gained or lost H3K27ac loops. We have now added the MA plot for differential H3K27ac HiChIP loop analysis between WT and KO BMDCs as Supplementary Fig. 6c.
We hope that this explanation clarifies the reviewer's point. Comment #18: Figure 4H should have an indication of the n for the experiment, and Figure 4I needs molecular weight markers and an indication of how many blots were performed.

Response #18:
We thank the reviewer for this suggestion. The number of biological replicates for Fig. 4h and 4i was described at the corresponding figure legend, and molecular weight markers were labeled in Fig. 4i.

Comment #19:
Supplemental Figure 5E does not show a log2(fold-change). Is this an RT-qPCR experiment?

Response #19:
We apologize that we did not describe the graph adequately. We now changed the legend of Supplementary Fig. 6f (corresponding to Supplementary Fig. 5e in the original version of the manuscript).
Comment #20: The analysis in Figure 5G is very useful to the reader and is a great example of how to dive deeper into Gene Ontology analyses. Are these all the genes in the "Regulation of NF-kB activity" term? If not, it would be useful to see all of them together on the graph.

Response #20:
We thank the reviewer for this comment. All the genes in the "Regulation of NF-κB activity" term were listed in Fig. 5g.

Response #21:
As suggested, we have now changed the legend for Fig. 6j and 6k from "H3K27ac loop" to "H3K27ac HiChIP loop". We apologize for the lack of information regarding the LOLA algorithm, and we have now added a brief description about that in the Methods section of the revised manuscript.

Comment #22:
Why are the FDR significance thresholds different for the significant loops between the H3K27ac and RelA HiChIP experiments? Some commentary on this would provide deeper insight into the technical details of these experiments.

Response #22:
HiChIP is a method used to study chromatin contacts mediated by specific proteins, such as architectural proteins, cell type-specific transcription factors, or histone modifications.
In this study, loop-calling for the RelA HiChIP experiment was performed using FitHiChIP with default parameter settings (FDR <0.01). However, we believe that more stringent criteria (FDR <10 −5 ) were required for loop-calling for the H3K27ac HiChIP experiment given that H3K27ac histone modification, unlike transcription factors with sharp and narrow peaks, frequently generates broad peaks and that lots of noise interactions could be considered as significant loops connecting anchors with low-signal H3K27ac located in the broad peak area.

Comment #23:
Figures 7G-H are not called out in the main text.